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Of Muffins and Machine Learning Models

Cloudera

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

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MLOps and the evolution of data science

IBM Big Data Hub

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

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Accelerating scope 3 emissions accounting: LLMs to the rescue

IBM Big Data Hub

Some companies attempt to estimate Scope 3 emissions by collecting data from suppliers and manually categorizing data, but progress is hindered by challenges such as large supplier base, depth of supply chains, complex data collection processes and substantial resource requirements.

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Artificial Intelligence: Implications On Marketing, Analytics, And You

Occam's Razor

Machine Learning | Marketing. Machine Learning | Analytics. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Machine Learning | Marketing.

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AI this Earth Day: Top opportunities to advance sustainability initiatives

IBM Big Data Hub

The US City of Atlanta , for example, uses IBM data collection, machine learning and AI to monitor public transit tunnel ventilation systems and predict potential failures that could put passengers at risk. This will help advance progress by optimizing resources used.

IoT 85
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R vs Python: What’s the Best Language for Natural Language Processing?

Sisense

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. Again, the library you use will be based on your use case.

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AI in marketing: How to leverage this powerful new technology for your next campaign

IBM Big Data Hub

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?